Field of the Invention
The present invention relates to an image processing technique to reduce color noise.
Description of the Related Art
It is known that the data of a color image captured by an image capturing device, such as a digital camera, is subjected to image processing in general after being separated into a luminance signal representing brightness and a color difference signal representing a color difference of each color component. Further, in recent years, the image capturing device, such as a digital camera, is demanded to provide an image of high quality. In particular, the request for high-sensitive photographing is strong in recent years and it is demanded to obtain an image of high quality with low noise even in a dark place or at night. However, in an environment where it is not possible to obtain a sufficient S/N ratio, such as in a dark place or at night, the noise of a color difference signal (color noise) appears as low-frequency random noise, and therefore, the image quality deteriorates.
In order to suppress the color noise, the smoothing processing using an averaging filter, a Gaussian filter, etc., or the color noise reduction processing using an order statistics filter, such as a median filter, is performed conventionally. However, in the case where the smoothing processing or the order statistics filter is used, it is necessary to design the filter so as to have a large number of taps in order to sufficiently reduce noise (low-frequency noise) in a large range, and therefore, an increase in the circuit scale will result. In view of this point, a method of obtaining the same effect without increasing the number of taps by performing filter processing after reducing an input image has been proposed (see Japanese Patent Laid-Open No. 2010-157163).
There is a case where color blurring occurs in the vicinity of an edge at the time of reducing color noise of an input image. For example, it is possible to reduce color noise in a large range by performing filter processing after reducing the input image, but color blurring will occur at the boundary of the color area due to enlargement of the reduced image. Further, also in the case where color noise is reduced without reducing the input image, it becomes more likely that color blurring occurs at the boundary portion due to the color noise reduction in a large range.